This paper constructs a physical model of carbon benefits and economic benefits of grid investment, as well as a virtual mapping relationship model from three levels: direct mapping, computational mapping, and inferential mapping. Based on the minimization of energy consumption cost and considering the constraints of benefit matching degree, the economic co-optimization model is designed. With the maximization of economic benefits as the optimization goal, the virtual model is realized as a closed loop of simulation, evaluation, analysis and co-optimization calculation. With the digital twin model as the framework, carbon emission cost, carbon trading cost, carbon governance cost, and total carbon cost are calculated, and the carbon benefit architecture of power grid equipment is analyzed to achieve the optimization of investment carbon benefit, considering the uncertainty in the process of equipment operation. With the digital twin as the core of the platform, we realize the carbon – economic collaborative deduction, quantitative analysis and management, and the optimal scheme at the level of integrated co-simulation. In the optimal Pareto frontier validation, the digital twin model carbon emission reduction rises from 85.2 tons in 1 million yuan to 1923 tons in 31 million yuan, with a maximum time of 19.5 s, while the particle swarm algorithm and the big data analysis require a maximum time of 38.3 s and 40.7 s. The transmission process emission reduction benefits of the digital twin model, the particle swarm optimization, and the big data analysis for the transmission process in 2024 are 402/104, 239/104t, and 379/104t, which is comprehensively better than the comparison method, and verifies the feasible path to realize the synergistic gain of carbon benefit and economic benefit when the digital twin model is used.
